What the data for this category looks like
Data for urban public transit declaration materials and case review comes from internal bus enterprise operation archives, administrative approval declaration documents, and vehicle and route management ledgers. Update frequency varies by material type. Daily declaration materials are updated as submitted. Annual cases are archived quarterly. Most documents are in Word format. A single material includes route direction descriptions, passenger flow statistics tables, and cost calculation attachments. Fields include route number, station list, approved passenger capacity, application date, and approval node. Units include kilometers, passenger trips, yuan, and other standard units.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Urban public transit declaration materials are mostly large Word files with tables and images. Single materials have many fields and inconsistent units. This increases context parsing pressure during multi-turn dialogue. Accurate matching of fields such as route number and approved passenger capacity requires prompts to clearly define field boundaries. This avoids information confusion. Slow parsing of large files extends multi-turn dialogue response cycles. The size of document blocks loaded per turn must be limited. Case batches have large format differences. Prompts must adapt to diverse document structures. They must also support on-demand calls to the latest updated operation archive data.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the mixed table and text structure of public transit declaration materials, avoids information breakage caused by table splitting |
| Overlap Length | 100–150 characters | Retains cross-block field context. For example, route numbers can be fully identified when spanning blocks |
| Single Search Limit | Top 6 entries | Relevant material entries for public transit cases are concentrated. Too many entries increase context load |
| Maximum Context | 6000–8000 tokens | Carries declaration material fragments and approval history in multi-turn dialogue, avoids exceeding model context limits |
| Question Optimization | Enabled | Simplifies vague user questions about case fields, accurately matches corresponding content in the knowledge base |
| Associated Knowledge Base | Bound to urban public transit operation archive library | Ensures the latest route, vehicle, and approval data is called during dialogue |
Three common mistakes
- Phenomenon: Word documents over 10 MB take more than 30 seconds to parse. The debug interface shows loading timeout. Cause: The chunking strategy is not adjusted for the table and image structure of public transit declaration materials. This results in an overly large single block size.
- Phenomenon: The corresponding relationship between route numbers and approved passenger capacity cannot be accurately matched during dialogue. Returned result fields are disordered. Cause: The prompt does not clearly define field extraction boundaries. It also does not associate the field mapping rules of the corresponding knowledge base.
- Phenomenon: An error "parameter format exception" is displayed in the debug preview after input guidance is enabled. Cause: The custom thesaurus input format does not comply with FastGPT verification rules. Standard option separators are not used.
How to confirm configurations are properly set
- Upload a single public transit declaration Word document over 10 MB. Check whether parsing time meets expectations.
- Enter a vague question, such as "XX route declaration materials from March 2024". Check whether the dialogue accurately matches the field information of the corresponding case.
- Enable the input guidance function. Enter test content in the debug preview interface. Confirm no error prompts are displayed.
- Check whether the
variablesparameter passes business parameters such as the route number bound to the current conversation. Confirm themessagesarray stores interactive content in conversation order. ConfirmchatIdis bound to the exclusive conversation context of a single case.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.